Multiple Linear Regression - Estimated Regression Equation
3m-6m[t] = + 32498.0476680317 + 0.199116284504935`-1m`[t] + 0.0268146129898515`1m-3m`[t] + 0.428394930834743`6m-1j`[t] + 0.430633053122037`1j-2j`[t] -0.226697521855814`2j-3j`[t] + 1.2443482240102`3j-5j`[t] + 0.347389136899369`5j-10j`[t] -3.17922405388549`10j+`[t] -9159.78115458565M1[t] -13204.2965852239M2[t] -30939.3093363493M3[t] -30171.1289062497M4[t] -28150.5289071723M5[t] -25476.2251719392M6[t] -39203.7428121068M7[t] -36480.4915457175M8[t] -34931.5534137446M9[t] -17797.7696809109M10[t] -11624.6972524238M11[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)32498.047668031718547.0810041.75220.0846850.042343
`-1m`0.1991162845049350.0967992.0570.0438990.02195
`1m-3m`0.02681461298985150.0854040.3140.7545940.377297
`6m-1j`0.4283949308347430.0584077.334600
`1j-2j`0.4306330531220370.0742345.80100
`2j-3j`-0.2266975218558140.073236-3.09540.0029490.001474
`3j-5j`1.24434822401020.235375.28682e-061e-06
`5j-10j`0.3473891368993690.2157111.61040.1123820.056191
`10j+`-3.179224053885490.660491-4.81341e-055e-06
M1-9159.781154585651807.221306-5.06844e-062e-06
M2-13204.29658522391209.39241-10.918100
M3-30939.30933634931469.65485-21.052100
M4-30171.12890624971720.856106-17.532600
M5-28150.52890717231747.380285-16.110100
M6-25476.22517193921874.184875-13.593200
M7-39203.74281210683928.461193-9.979400
M8-36480.49154571753104.081234-11.752400
M9-34931.55341374463127.088768-11.170600
M10-17797.76968091092035.76673-8.742500
M11-11624.69725242381787.021905-6.505100


Multiple Linear Regression - Regression Statistics
Multiple R0.985976067115517
R-squared0.972148804924583
Adjusted R-squared0.963613761272438
F-TEST (value)113.900859157337
F-TEST (DF numerator)19
F-TEST (DF denominator)62
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1916.88677630193
Sum Squared Residuals227816204.615995


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
18236881221.45933979161146.54066020842
27779577270.9675135052524.032486494852
36282761891.5790027378935.420997262191
46719763227.82209540843969.17790459157
56684865069.85956440051778.14043559954
66642167448.8595273246-1027.8595273246
76064364222.0259842818-3579.02598428177
85907158730.7263083186340.273691681425
95874660530.4399812848-1784.43998128483
106851565852.46458665182662.5354133482
116899866862.11053100282135.88946899717
127761478662.9998379133-1048.99983791326
137346974396.9556279241-927.955627924105
146714569368.771287931-2223.77128793096
155110952012.4615355735-903.461535573485
165113053269.7339220951-2139.73392209506
174954451952.3402637549-2408.34026375487
185073050222.8011135774507.198886422644
194971047954.28971840341755.71028159658
205005951268.3559021415-1209.35590214146
214968148346.53960368721334.46039631285
226577363916.20087630531856.79912369472
236612964555.18613639761573.81386360236
247803977179.1829174994859.817082500645
257127873024.2009012237-1746.20090122369
266586267124.4596726704-1262.45967267038
275154050111.04606786861428.95393213143
285151353292.9858339028-1779.98583390281
294974049848.2196215016-108.219621501609
305098053470.1255023997-2490.12550239969
315129450249.08028873171044.91971126827
324971948836.6174938092882.382506190831
335067348186.34890544912486.65109455088
345919160354.5936671182-1163.59366711823
356180764570.0335679256-2763.03356792557
367768780740.671051561-3053.67105156098
377722778558.4167203705-1331.41672037054
387559475014.6485181486579.351481851426
396415862335.31593694251822.68406305753
406455165217.4885370419-666.488537041903
416514363985.49087845171157.50912154832
426995868994.6138402869963.386159713119
436815464537.89616427693616.10383572307
446462862089.33187783332538.66812216673
456169062206.1931163004-516.193116300362
467141270778.5375941554633.462405844628
477360673970.1946743112-364.194674311227
489158690568.13870238881017.86129761122
498529986212.9507665043-913.950766504315
508175279766.41503901941985.58496098059
516347964396.2167833079-917.21678330791
526247063081.2067583267-611.206758326699
536045261572.478250632-1120.47825063203
546559364877.4275589551715.572441044896
556422365913.1242286992-1690.12422869917
566146663418.9641237363-1952.96412373632
575847160956.1758601742-2485.17586017416
586726169699.5863127586-2438.58631275861
597182671027.5101939673798.489806032715
608469584059.1893319186635.810668081372
618055879420.07619949041137.92380050959
627375574113.731077646-358.731077645961
635778658802.2646734808-1016.26467348083
645926658445.874562953820.125437047035
655881557845.3830854839969.616914516136
666094558494.23740635352450.76259364647
675852057876.1795142217643.820485778332
685974757290.33344024482456.66655975521
695640155318.5942379961082.40576200402
706477365443.2924552088-670.292455208796
716802669406.9648963954-1380.96489639545
728428882698.8181587191589.181841281
738417481538.94044469542635.05955530465
747861877862.0068910796755.993108920429
756118562535.1160000889-1350.11600008893
766361263203.8882902721408.111709727864
776267362941.2283357755-268.22833577549
786454965667.9350511028-1118.93505110283
796110362894.4041013853-1791.40410138531
806104764102.6708539164-3055.67085391642
816158961706.7082951084-117.708295108394
827123372113.3245078019-880.324507801906


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
230.02703395605433530.05406791210867050.972966043945665
240.4770620251400310.9541240502800620.522937974859969
250.6991485568565170.6017028862869660.300851443143483
260.596002696040450.8079946079191010.40399730395955
270.5159161817201970.9681676365596060.484083818279803
280.5063790185517110.9872419628965770.493620981448289
290.4128802316163380.8257604632326750.587119768383662
300.435854446624960.871708893249920.56414555337504
310.3842521503598760.7685043007197530.615747849640124
320.3202855560143950.640571112028790.679714443985605
330.339474811558630.678949623117260.66052518844137
340.7768141516044540.4463716967910930.223185848395546
350.8193198309347120.3613603381305760.180680169065288
360.8797622392503550.240475521499290.120237760749645
370.9254309489055740.1491381021888530.0745690510944263
380.9804058723069980.03918825538600350.0195941276930018
390.9813515075617770.03729698487644520.0186484924382226
400.9901814351827990.01963712963440120.0098185648172006
410.9875064956107720.02498700877845640.0124935043892282
420.9883551620945130.0232896758109730.0116448379054865
430.9872061067516760.02558778649664710.0127938932483235
440.9884094282131730.02318114357365330.0115905717868267
450.9830542588585640.03389148228287170.0169457411414358
460.9716032063718010.05679358725639840.0283967936281992
470.9518660943793440.09626781124131230.0481339056206562
480.9857190769391880.02856184612162340.0142809230608117
490.9765965043731830.04680699125363430.0234034956268172
500.9966989291226820.006602141754636310.00330107087731816
510.9973135280615410.005372943876917190.0026864719384586
520.9937031121207620.01259377575847510.00629688787923757
530.9896822453638830.02063550927223350.0103177546361167
540.977442671714540.04511465657092040.0225573282854602
550.9699237542355110.06015249152897860.0300762457644893
560.9620718875461430.07585622490771350.0379281124538567
570.9959711878019010.008057624396198780.00402881219809939
580.9896945803899770.02061083922004520.0103054196100226
590.9640343108253510.07193137834929890.0359656891746494


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level30.0810810810810811NOK
5% type I error level170.459459459459459NOK
10% type I error level230.621621621621622NOK